Triple
T17364114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Region of Cameroon |
E422142
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Muyuka |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Muyuka | Statement: [Southwest Region of Cameroon, containsTown, Muyuka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muyuka Context triple: [Southwest Region of Cameroon, containsTown, Muyuka]
-
A.
Muyuka
chosen
Muyuka is a town in Cameroon known as an agricultural and trading center in the country's Anglophone southwest.
-
B.
Muyil
Muyil is an ancient Maya archaeological site in Mexico’s Yucatán Peninsula, known for its well-preserved temples and proximity to the Sian Ka'an Biosphere Reserve.
-
C.
Yunguyo
Yunguyo is a Peruvian town situated on the shores of Lake Titicaca near the border with Bolivia.
-
D.
Maruca
Maruca is the nickname of María Antonieta Hagenaar, known primarily as the wife of Mexican muralist David Alfaro Siqueiros.
-
E.
Mokuola
Mokuola is a small, lush island in Hilo Bay on Hawaii’s Big Island, known for its tranquil park, tidal pools, and scenic views of the bay and Mauna Kea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4f52988190847230e119a35b87 |
completed | April 19, 2026, 2:13 a.m. |
Created at: April 10, 2026, 5:44 a.m.